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https://github.com/kmkurn/pytorch-crf

(Linear-chain) Conditional random field in PyTorch.
https://github.com/kmkurn/pytorch-crf

conditional-random-fields neural-networks pytorch

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(Linear-chain) Conditional random field in PyTorch.

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pytorch-crf
===========

Conditional random field in `PyTorch `_.

.. image:: https://img.shields.io/pypi/pyversions/pytorch-crf.svg?style=flat
:target: https://img.shields.io/pypi/pyversions/pytorch-crf.svg?style=flat
:alt: Python versions

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:target: https://pypi.org/project/pytorch-crf
:alt: PyPI project

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:target: https://github.com/kmkurn/pytorch-crf/actions/workflows/run_tests.yml
:alt: Build status

.. image:: https://img.shields.io/readthedocs/pytorch-crf.svg?style=flat
:target: https://pytorch-crf.readthedocs.io
:alt: Documentation status

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:target: https://coveralls.io/github/kmkurn/pytorch-crf
:alt: Code coverage

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:target: https://choosealicense.com/licenses/mit/
:alt: License

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:target: http://spacemacs.org
:alt: Built with Spacemacs

This package provides an implementation of linear-chain `conditional random field
`_ (CRF) in PyTorch.
This implementation borrows mostly from `AllenNLP CRF module
`_ with some modifications.

Documentation
=============

https://pytorch-crf.readthedocs.io/

License
=======

MIT

Contributing
============

Contributions are welcome! Please follow these instructions to install
dependencies and running the tests and linter.

Installing dependencies
-----------------------

Make sure you setup a virtual environment with Python. Then, install all
the dependencies in ``requirements.txt`` file and install this package in
development mode.

::

pip install -r requirements.txt
pip install -e .

Setup pre-commit hook
---------------------

Simply run::

ln -s ../../pre-commit.sh .git/hooks/pre-commit

Running tests
-------------

Run ``pytest`` in the project root directory.

Running linter
--------------

Run ``flake8`` in the project root directory. This will also run ``mypy``,
thanks to ``flake8-mypy`` package.